Data Engineer
London • Permanent • Office-based
About Our Client
Our client is a technology-focused organisation working with complex healthcare data, building robust data products that are used in real-world settings. Their work sits at the intersection of engineering, data and healthcare, and their team is focused on solving practical problems such as acquiring, structuring and validating large-scale data so it can be trusted and used. Joining our client’s team means working closely with people who care about production-quality pipelines, clean schemas and usable interfaces rather than proofs of concept that never ship.
The Opportunity
This role is ideal if you enjoy building end-to-end data solutions: from scraping and acquisition, through ETL/ELT, to the interface that lets others actually use what you have built. You will spend most of your time in production code, not notebooks, and you will use AI inside pipelines for tangible outcomes such as extraction, classification and validation, rather than experimental model training. You will have ownership over how healthcare data is normalised, resolved and exposed in a way that supports meaningful decisions, and you will be trusted to ship working systems that our client’s team and their customers can rely on.
Key Responsibilities
• Design, build and maintain production-grade ETL/ELT pipelines using Python and SQL.
• Implement AI-powered components within data pipelines for structured extraction, classification and validation.
• Work with prompt engineering and APIs to integrate AI capabilities effectively, without focusing on training models.
• Develop data scraping and acquisition processes capable of operating at scale.
• Handle healthcare data with care and rigour, ensuring quality, consistency and compliance with relevant standards.
• Design and evolve data schemas to support normalisation, deduplication and entity resolution inside pipelines.
• Build and ship back-end services that expose data reliably to downstream applications.
• Create a usable front-end interface on top of your pipelines so stakeholders can interact with and benefit from the data products.
• Collaborate with our client’s team to iterate on data solutions and improve existing pipelines.
What Our Client Is Looking For
• Must have experience as founding engineer/developer or start up experience• Strong hands-on experience building ETL/ELT pipelines in production environments.
• Proficiency in Python and SQL, with a focus on writing maintainable, testable code rather than exploratory notebooks.
• Experience using AI within data workflows, particularly prompt engineering and working with APIs for extraction and classification tasks.
• Background in large-scale data scraping or acquisition, with an understanding of performance and reliability considerations.
• Familiarity with working on healthcare or similarly sensitive, structured data sets.
• Ability to design schemas and implement normalisation, deduplication and entity resolution within pipelines.
• Comfort working across both back-end and front-end, enabling you to deliver a functional interface on top of the data layer.
• A practical, delivery-focused mindset with an interest in seeing data systems used in production rather than remaining as prototypes.
What You’ll Gain
• The chance to own full data workflows, from ingestion to interface, and see your work operating in a real healthcare context.
• Exposure to modern AI tooling in a grounded way, using it where it adds value inside production pipelines.
• Opportunities to work closely with experienced engineers and data specialists in our client’s team, learning from complex data challenges.
• A role that allows you to influence data architecture and the way healthcare data is structured and made usable.
How To Apply
If you are a Data Engineer who enjoys building real systems, using Python and SQL to create robust pipelines, and you want to work with healthcare data where AI is applied for practical outcomes, we would like to hear from you. Please submit your CV, and we will be in touch to discuss the role and our client’s team in more detail.